Question 3 Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. Rocker and coworkers¹ developed a logistic regression model for predicting ARDS in a patient based on three variables: ● ● PI Protein accumulation index. O Arterial oxygen in kPa. ● A Age in years. Some of the output from the SPSS calculation for this model is given below. Omnibus Testª Parameter (Intercept) Likelihood Ratio Chi- Square 58.418 Protein Accumulation Index 3 Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Compares the fitted model against the intercept-only model. df B 6.649 1.554 -.498 -.057 1ª Std. Error 2.2453 4371 Sig. .1631 .0257 .000 Lower 95% Wald Confidence Interval 2.249 .697 Parameter Estimates Arterial Oxygen/kPa Age / years (Scale) Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Fixed at the displayed value. -.818 -.107 Upper 11.050 2.411 -.179 -.006 Source (Intercept) Protein Accumulation Index Arterial Oxygen/kPa Age / years Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years Hypothesis Test Wald Chi- Square Tests of Model Effects 8.770 12.643 9.330 4.848 df 1 1 Wald Chi- Square 1 1 8.770 12.643 9.330 4.848 Sig. Type III df .002 .028 Exp(B) .003 772.219 .000 4.731 .608 .945 1 1 Sig. 1 1 .003 .000 .002 .028 95% Wald Confidence Interval for Exp(B) Lower 9.474 2.009 .441 .898 a) Comment on the overall significance of the model. b) Comment on whether or not there is there evidence that the Protein Accumulation Index is associated with ARDS. Upper 62941.590 11.143 c) By considering the model coefficients, comment on how each of the three variables affects the probability of a patient having ARDS. .837 .994
Question 3 Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. Rocker and coworkers¹ developed a logistic regression model for predicting ARDS in a patient based on three variables: ● ● PI Protein accumulation index. O Arterial oxygen in kPa. ● A Age in years. Some of the output from the SPSS calculation for this model is given below. Omnibus Testª Parameter (Intercept) Likelihood Ratio Chi- Square 58.418 Protein Accumulation Index 3 Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Compares the fitted model against the intercept-only model. df B 6.649 1.554 -.498 -.057 1ª Std. Error 2.2453 4371 Sig. .1631 .0257 .000 Lower 95% Wald Confidence Interval 2.249 .697 Parameter Estimates Arterial Oxygen/kPa Age / years (Scale) Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Fixed at the displayed value. -.818 -.107 Upper 11.050 2.411 -.179 -.006 Source (Intercept) Protein Accumulation Index Arterial Oxygen/kPa Age / years Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years Hypothesis Test Wald Chi- Square Tests of Model Effects 8.770 12.643 9.330 4.848 df 1 1 Wald Chi- Square 1 1 8.770 12.643 9.330 4.848 Sig. Type III df .002 .028 Exp(B) .003 772.219 .000 4.731 .608 .945 1 1 Sig. 1 1 .003 .000 .002 .028 95% Wald Confidence Interval for Exp(B) Lower 9.474 2.009 .441 .898 a) Comment on the overall significance of the model. b) Comment on whether or not there is there evidence that the Protein Accumulation Index is associated with ARDS. Upper 62941.590 11.143 c) By considering the model coefficients, comment on how each of the three variables affects the probability of a patient having ARDS. .837 .994
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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